Online user behavioral analytics are used by advertisers, advertisement networks, and other content providers for targeting online advertisements, offers, suggestions, and other digital content to particular audiences. In many implementations, online user behavioral analytics are collected and generated by a content server and/or an independent behavioral analytics server (i.e., the user behavioral analytics are server-based). To do so, the server monitors the behavior of the user while interacting with the analytics server, other servers monitored by the analytics server, and/or monitored online services provided to the user. Based on the user's behavior and preferences, the behavioral analytics server may determine which advertisements to present to the user, which products to suggest to the user, how to structure an online interface, and/or which other digital content to provide to the user.
Because the behavioral analytics servers monitor the user's interaction with the particular server and/or with other specific, monitored servers or services, typical user behavioral analytics are content-dependent and/or source-dependent. That is, only the user's behavior with the particular monitored servers or services are considered. For example, an online bookseller may be able to determine a user's preference for books based on past viewing and purchases, but is unable to make any further inferences based on the user's preference for other content such as movies and songs. As such, typical server-based behavioral analytics have a limited scope and may not fully represent a user's behavior and preferences.